from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
measurements = ['iteration_throughput', 'latency', 'mean_duration_sklearn', 'mean_duration_sklearnex', 'speedup', 'std_duration_sklearn', 'std_duration_sklearnex', 'std_speedup']
def get_position(string):
if "mean_duration" in string:
return 3
elif "std_duration" in string:
return 2
elif "score" in string:
return 1
elif "speedup" in string:
return 0
else:
return -1
sorted(measurements, key=get_position, reverse=True)
['mean_duration_sklearn', 'mean_duration_sklearnex', 'std_duration_sklearn', 'std_duration_sklearnex', 'speedup', 'std_speedup', 'iteration_throughput', 'latency']
reporting = HpMatchReporting(against_lib="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 1.951474 | 0.179328 | NaN | 0.000410 | 0.001951 | brute | -1 | 1 | 0.663 | 0.169336 | 0.007575 | 0.687 | 11.524242 | 11.535767 | 0.024 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 22d5eac4a4146149b35eae6914921514 | 2cf49829391aa7891e877f2ed070adf0 | 2.721689 | 0.029252 | NaN | 0.000294 | 0.002722 | brute | -1 | 5 | 0.757 | 0.170137 | 0.002389 | 0.742 | 15.997088 | 15.998665 | 0.015 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 2.064564 | 0.003485 | NaN | 0.000387 | 0.002065 | brute | 1 | 100 | 0.882 | 0.205597 | 0.000490 | 0.875 | 10.041787 | 10.041815 | 0.007 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 0.022841 | 0.000331 | NaN | 0.000035 | 0.022841 | brute | 1 | 100 | 1.000 | 0.008809 | 0.000219 | 0.000 | 2.592934 | 2.593735 | 1.000 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 2.765083 | 0.021127 | NaN | 0.000289 | 0.002765 | brute | -1 | 100 | 0.882 | 0.207966 | 0.004242 | 0.875 | 13.295860 | 13.298626 | 0.007 |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 0.024224 | 0.003025 | NaN | 0.000033 | 0.024224 | brute | -1 | 100 | 1.000 | 0.008989 | 0.000771 | 0.000 | 2.694897 | 2.704790 | 1.000 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 2.046789 | 0.002251 | NaN | 0.000391 | 0.002047 | brute | 1 | 5 | 0.757 | 0.168089 | 0.000189 | 0.742 | 12.176808 | 12.176816 | 0.015 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | b79d63bb7670c492de5c3befac58fe29 | 2cf49829391aa7891e877f2ed070adf0 | 1.221240 | 0.041680 | NaN | 0.000655 | 0.001221 | brute | 1 | 1 | 0.663 | 0.167715 | 0.000769 | 0.687 | 7.281648 | 7.281725 | 0.024 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 1.726383 | 0.025467 | NaN | 0.000009 | 0.001726 | brute | -1 | 1 | 0.896 | 0.025483 | 0.000099 | 0.967 | 67.745479 | 67.745988 | 0.071 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 22d5eac4a4146149b35eae6914921514 | 88843f54689e3271092f70126e1de585 | 2.610355 | 0.024594 | NaN | 0.000006 | 0.002610 | brute | -1 | 5 | 0.922 | 0.026602 | 0.000407 | 0.974 | 98.126578 | 98.138068 | 0.052 |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 16f94fc93942ff7ece860c9b0f64645f | 88843f54689e3271092f70126e1de585 | 1.970619 | 0.002506 | NaN | 0.000008 | 0.001971 | brute | 1 | 100 | 0.929 | 0.059669 | 0.001612 | 0.975 | 33.026029 | 33.038084 | 0.046 |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2d5f2b2c02d77766434d9e5033b4a76c | 88843f54689e3271092f70126e1de585 | 2.636970 | 0.022323 | NaN | 0.000006 | 0.002637 | brute | -1 | 100 | 0.929 | 0.059686 | 0.001518 | 0.975 | 44.180964 | 44.195255 | 0.046 |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | efac583623711d395ddae7a1e881ff68 | 88843f54689e3271092f70126e1de585 | 1.946543 | 0.001387 | NaN | 0.000008 | 0.001947 | brute | 1 | 5 | 0.922 | 0.026544 | 0.000196 | 0.974 | 73.331700 | 73.333696 | 0.052 |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | b79d63bb7670c492de5c3befac58fe29 | 88843f54689e3271092f70126e1de585 | 1.082449 | 0.008280 | NaN | 0.000015 | 0.001082 | brute | 1 | 1 | 0.896 | 0.025576 | 0.000072 | 0.967 | 42.322488 | 42.322658 | 0.071 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.581 | 0.0 | -1 | 1 | 0.050 | 0.005 | 0.245 | 0.247 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.765 | 0.0 | -1 | 5 | 0.048 | 0.001 | 0.245 | 0.245 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.596 | 0.0 | 1 | 100 | 0.048 | 0.001 | 0.254 | 0.254 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.441 | 0.0 | -1 | 100 | 0.048 | 0.001 | 0.261 | 0.261 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.602 | 0.0 | 1 | 5 | 0.048 | 0.001 | 0.254 | 0.254 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.012 | 0.0 | 6.514 | 0.0 | 1 | 1 | 0.048 | 0.000 | 0.257 | 0.257 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.362 | 0.0 | -1 | 1 | 0.008 | 0.000 | 0.527 | 0.527 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.367 | 0.0 | -1 | 5 | 0.008 | 0.000 | 0.520 | 0.520 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.374 | 0.0 | 1 | 100 | 0.008 | 0.000 | 0.510 | 0.510 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.364 | 0.0 | -1 | 100 | 0.008 | 0.000 | 0.524 | 0.525 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.376 | 0.0 | 1 | 5 | 0.008 | 0.000 | 0.506 | 0.506 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.365 | 0.0 | 1 | 1 | 0.008 | 0.000 | 0.522 | 0.522 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.951 | 0.179 | 0.000 | 0.002 | -1 | 1 | 0.169 | 0.008 | 11.524 | 11.536 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | 0.000 | 0.025 | -1 | 1 | 0.009 | 0.000 | 2.899 | 2.900 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.722 | 0.029 | 0.000 | 0.003 | -1 | 5 | 0.170 | 0.002 | 15.997 | 15.999 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | 0.000 | 0.025 | -1 | 5 | 0.009 | 0.000 | 2.866 | 2.866 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.065 | 0.003 | 0.000 | 0.002 | 1 | 100 | 0.206 | 0.000 | 10.042 | 10.042 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.000 | 0.000 | 0.023 | 1 | 100 | 0.009 | 0.000 | 2.593 | 2.594 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.765 | 0.021 | 0.000 | 0.003 | -1 | 100 | 0.208 | 0.004 | 13.296 | 13.299 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.003 | 0.000 | 0.024 | -1 | 100 | 0.009 | 0.001 | 2.695 | 2.705 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.047 | 0.002 | 0.000 | 0.002 | 1 | 5 | 0.168 | 0.000 | 12.177 | 12.177 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.001 | 0.000 | 0.023 | 1 | 5 | 0.009 | 0.000 | 2.608 | 2.608 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.221 | 0.042 | 0.001 | 0.001 | 1 | 1 | 0.168 | 0.001 | 7.282 | 7.282 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.022 | 0.000 | 0.000 | 0.022 | 1 | 1 | 0.009 | 0.000 | 2.508 | 2.509 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.726 | 0.025 | 0.000 | 0.002 | -1 | 1 | 0.025 | 0.000 | 67.745 | 67.746 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | -1 | 1 | 0.001 | 0.000 | 5.696 | 5.704 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.610 | 0.025 | 0.000 | 0.003 | -1 | 5 | 0.027 | 0.000 | 98.127 | 98.138 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.002 | 0.000 | 0.006 | -1 | 5 | 0.001 | 0.000 | 9.829 | 9.850 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.971 | 0.003 | 0.000 | 0.002 | 1 | 100 | 0.060 | 0.002 | 33.026 | 33.038 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 4.089 | 4.103 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.637 | 0.022 | 0.000 | 0.003 | -1 | 100 | 0.060 | 0.002 | 44.181 | 44.195 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.004 | 0.000 | 0.006 | -1 | 100 | 0.001 | 0.000 | 8.465 | 8.499 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.947 | 0.001 | 0.000 | 0.002 | 1 | 5 | 0.027 | 0.000 | 73.332 | 73.334 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 4.479 | 4.483 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.082 | 0.008 | 0.000 | 0.001 | 1 | 1 | 0.026 | 0.000 | 42.322 | 42.323 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.750 | 2.759 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.779112 | 1.022175 | NaN | 0.000103 | 0.000779 | kd_tree | -1 | 1 | 0.929 | 0.110197 | 0.002212 | 0.910 | 7.070186 | 7.071610 | 0.019 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | dc74b969bf622bc24ba3bc62c980983b | 1eb6cf1a720a225efb91df0b529b0510 | 0.989423 | 0.360718 | NaN | 0.000081 | 0.000989 | kd_tree | -1 | 5 | 0.946 | 0.192088 | 0.003080 | 0.941 | 5.150893 | 5.151556 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 5.436315 | 0.537301 | NaN | 0.000015 | 0.005436 | kd_tree | 1 | 100 | 0.951 | 0.582351 | 0.008237 | 0.940 | 9.335121 | 9.336054 | 0.011 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 022f7445d43bb1dbc24dc3106c03cb93 | 1eb6cf1a720a225efb91df0b529b0510 | 2.904067 | 0.263187 | NaN | 0.000028 | 0.002904 | kd_tree | -1 | 100 | 0.951 | 0.602179 | 0.030179 | 0.940 | 4.822601 | 4.828653 | 0.011 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 1.618465 | 0.201740 | NaN | 0.000049 | 0.001618 | kd_tree | 1 | 5 | 0.946 | 0.194173 | 0.003210 | 0.941 | 8.335178 | 8.336317 | 0.005 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | a9455565db1d8e052a783317c99744ff | 1eb6cf1a720a225efb91df0b529b0510 | 0.912997 | 0.326837 | NaN | 0.000088 | 0.000913 | kd_tree | 1 | 1 | 0.929 | 0.107503 | 0.001168 | 0.910 | 8.492755 | 8.493256 | 0.019 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.024846 | 0.013165 | NaN | 0.000644 | 0.000025 | kd_tree | -1 | 1 | 0.891 | 0.000405 | 0.000046 | 0.879 | 61.279851 | 61.677021 | 0.012 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | dc74b969bf622bc24ba3bc62c980983b | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.021764 | 0.001449 | NaN | 0.000735 | 0.000022 | kd_tree | -1 | 5 | 0.911 | 0.000659 | 0.000019 | 0.905 | 33.043209 | 33.057182 | 0.006 |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 41accfcdcd5c50784bedf6164b63de99 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.036308 | 0.013017 | NaN | 0.000441 | 0.000036 | kd_tree | 1 | 100 | 0.894 | 0.004508 | 0.000140 | 0.917 | 8.054845 | 8.058718 | 0.023 |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 022f7445d43bb1dbc24dc3106c03cb93 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.036362 | 0.007232 | NaN | 0.000440 | 0.000036 | kd_tree | -1 | 100 | 0.894 | 0.005663 | 0.000617 | 0.917 | 6.421526 | 6.459497 | 0.023 |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 84622ba45e941db642965553529e1941 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.019499 | 0.000223 | NaN | 0.000821 | 0.000019 | kd_tree | 1 | 5 | 0.911 | 0.000649 | 0.000032 | 0.905 | 30.039126 | 30.074742 | 0.006 |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | a9455565db1d8e052a783317c99744ff | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.017935 | 0.000134 | NaN | 0.000892 | 0.000018 | kd_tree | 1 | 1 | 0.891 | 0.000409 | 0.000028 | 0.879 | 43.847172 | 43.946977 | 0.012 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.877 | 0.194 | 0.028 | 0.0 | -1 | 1 | 0.764 | 0.128 | 3.768 | 3.821 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.551 | 0.162 | 0.023 | 0.0 | -1 | 5 | 0.722 | 0.013 | 4.918 | 4.919 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.535 | 0.169 | 0.023 | 0.0 | 1 | 100 | 0.701 | 0.004 | 5.041 | 5.041 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.455 | 0.058 | 0.023 | 0.0 | -1 | 100 | 0.728 | 0.029 | 4.743 | 4.747 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.569 | 0.200 | 0.022 | 0.0 | 1 | 5 | 0.710 | 0.010 | 5.027 | 5.027 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.426 | 0.035 | 0.023 | 0.0 | 1 | 1 | 0.706 | 0.006 | 4.853 | 4.853 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.022 | 0.0 | -1 | 1 | 0.004 | 0.003 | 0.173 | 0.207 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | -1 | 5 | 0.002 | 0.002 | 0.329 | 0.520 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 100 | 0.001 | 0.001 | 0.413 | 0.587 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.579 | 0.621 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.641 | 0.642 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.032 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.658 | 0.659 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.779 | 1.022 | 0.000 | 0.001 | -1 | 1 | 0.110 | 0.002 | 7.070 | 7.072 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.000 | 0.000 | 8.613 | 9.020 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.989 | 0.361 | 0.000 | 0.001 | -1 | 5 | 0.192 | 0.003 | 5.151 | 5.152 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 0.000 | 0.000 | 7.418 | 7.765 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.436 | 0.537 | 0.000 | 0.005 | 1 | 100 | 0.582 | 0.008 | 9.335 | 9.336 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 4.203 | 4.380 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2.904 | 0.263 | 0.000 | 0.003 | -1 | 100 | 0.602 | 0.030 | 4.823 | 4.829 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 0.001 | 0.000 | 6.372 | 6.637 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.618 | 0.202 | 0.000 | 0.002 | 1 | 5 | 0.194 | 0.003 | 8.335 | 8.336 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.000 | 0.000 | 3.498 | 3.627 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.913 | 0.327 | 0.000 | 0.001 | 1 | 1 | 0.108 | 0.001 | 8.493 | 8.493 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 3.830 | 4.043 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.025 | 0.013 | 0.001 | 0.000 | -1 | 1 | 0.000 | 0.000 | 61.280 | 61.677 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.000 | 0.000 | 24.386 | 25.403 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.022 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.001 | 0.000 | 33.043 | 33.057 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 22.177 | 23.617 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.036 | 0.013 | 0.000 | 0.000 | 1 | 100 | 0.005 | 0.000 | 8.055 | 8.059 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 6.193 | 6.495 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.036 | 0.007 | 0.000 | 0.000 | -1 | 100 | 0.006 | 0.001 | 6.422 | 6.459 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 20.488 | 21.738 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.019 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 30.039 | 30.075 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 6.186 | 6.549 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.018 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.000 | 0.000 | 43.847 | 43.947 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 6.115 | 6.475 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.515 | 0.085 | 30 | 0.031 | 0.0 | random | 0.370 | 0.027 | 1.390 | 1.393 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.556 | 0.014 | 30 | 0.029 | 0.0 | k-means++ | 0.408 | 0.029 | 1.362 | 1.365 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.673 | 0.129 | 30 | 0.141 | 0.0 | random | 2.960 | 0.116 | 1.917 | 1.918 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.868 | 0.015 | 30 | 0.136 | 0.0 | k-means++ | 3.243 | 0.039 | 1.809 | 1.809 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.009 | 0.000 | random | 0.0 | 0.0 | 8.301 | 15.174 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | random | 0.0 | 0.0 | 8.231 | 13.906 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.009 | 0.000 | k-means++ | 0.0 | 0.0 | 12.757 | 14.889 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | k-means++ | 0.0 | 0.0 | 14.387 | 15.823 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.460 | 0.000 | random | 0.0 | 0.0 | 6.750 | 7.257 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | random | 0.0 | 0.0 | 12.433 | 13.013 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.478 | 0.000 | k-means++ | 0.0 | 0.0 | 6.485 | 6.959 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | k-means++ | 0.0 | 0.0 | 14.279 | 14.836 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | diff_adjusted_rand_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 3db9c030f488d0e8ff350ae449da4627 | 058b7e3842b587a5c675518f0706f5ee | 0.001707 | 0.000046 | 20 | 0.009373 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.000126 | 0.000431 | 0.000032 | -0.000965 | 3.957344 | 3.968107 | 0.001090 |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | ac9b8cec4749455c0d1cd1a92c150716 | 058b7e3842b587a5c675518f0706f5ee | 0.001893 | 0.000405 | 20 | 0.008454 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.001245 | 0.000421 | 0.000026 | -0.000750 | 4.491481 | 4.500132 | 0.001995 |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 3db9c030f488d0e8ff350ae449da4627 | 7f85b913f395ec54101a6738ea63a9a7 | 0.002646 | 0.000276 | 20 | 0.302303 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.278733 | 0.000942 | 0.000063 | 0.293767 | 2.808728 | 2.815086 | 0.015034 |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | ac9b8cec4749455c0d1cd1a92c150716 | 7f85b913f395ec54101a6738ea63a9a7 | 0.002472 | 0.000149 | 20 | 0.323674 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.317011 | 0.000936 | 0.000066 | 0.256968 | 2.639918 | 2.646479 | 0.060044 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.073 | 0.000 | 20 | 0.002 | 0.0 | random | 0.026 | 0.004 | 2.771 | 2.797 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.212 | 0.002 | 20 | 0.001 | 0.0 | k-means++ | 0.080 | 0.000 | 2.657 | 2.657 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.197 | 0.002 | 20 | 0.041 | 0.0 | random | 0.104 | 0.001 | 1.892 | 1.892 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.564 | 0.008 | 20 | 0.014 | 0.0 | k-means++ | 0.289 | 0.002 | 1.950 | 1.950 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | random | 0.000 | 0.0 | 3.957 | 3.968 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | random | 0.000 | 0.0 | 13.729 | 14.207 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.008 | 0.000 | k-means++ | 0.000 | 0.0 | 4.491 | 4.500 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | k-means++ | 0.000 | 0.0 | 12.908 | 13.396 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.302 | 0.000 | random | 0.001 | 0.0 | 2.809 | 2.815 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | random | 0.000 | 0.0 | 10.981 | 11.153 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.324 | 0.000 | k-means++ | 0.001 | 0.0 | 2.640 | 2.646 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | k-means++ | 0.000 | 0.0 | 10.589 | 10.902 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | f11be2529b0a77bc8fb5ee8de141e6b2 | 09c36ed6521e03974d0c134895f56c01 | 0.000412 | 0.000448 | [20] | 1.941076 | 4.121426e-07 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.56 | 0.000864 | 0.001662 | 0.55 | 0.477067 | 1.034154 | 0.01 |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | f11be2529b0a77bc8fb5ee8de141e6b2 | 7daecaea01e5baa8c862f264e3c1c3b0 | 0.001628 | 0.000282 | [26] | 4.914008 | 1.627999e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.35 | 0.005126 | 0.001898 | 0.28 | 0.317605 | 0.338685 | 0.07 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 10.957 | 0.377 | [20] | 0.073 | 0.000 | 2.015 | 0.025 | 5.436 | 5.437 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 0.994 | 0.716 | [26] | 0.080 | 0.001 | 0.837 | 0.022 | 1.188 | 1.188 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 1.941 | 0.0 | 0.001 | 0.002 | 0.477 | 1.034 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.016 | 0.0 | 0.000 | 0.000 | 0.363 | 0.369 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 4.914 | 0.0 | 0.005 | 0.002 | 0.318 | 0.339 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 1.066 | 0.0 | 0.002 | 0.000 | 0.047 | 0.047 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | diff_r2_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | a70ae8dc5c059ec88cf27c61016aee2a | 14fae294d530397144c65ba3209bf125 | 0.01211 | 0.000371 | NaN | 6.606066 | 0.000012 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.082567 | 0.019495 | 0.000725 | 0.122191 | 0.621177 | 0.621606 | 0.039624 |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.181 | 0.003 | 0.442 | 0.0 | 0.185 | 0.00 | 0.977 | 0.977 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.158 | 0.077 | 0.691 | 0.0 | 0.311 | 0.28 | 3.725 | 5.018 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.0 | 6.606 | 0.0 | 0.019 | 0.001 | 0.621 | 0.622 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | 1.393 | 0.0 | 0.000 | 0.000 | 0.625 | 0.676 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | 5.143 | 0.0 | 0.000 | 0.000 | 0.566 | 0.745 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | 0.017 | 0.0 | 0.000 | 0.000 | 0.611 | 0.647 | See | See |